Skeleton clustering by autonomous mobile robots for subtle fall risk discovery

Yutaka Deguchi, Einoshin Suzuki

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

In this paper, we propose two new instability features, a data pre-processing method, and a new evaluation method for skeleton clustering by autonomous mobile robots for subtle fall risk discovery. We had proposed an autonomous mobile robot which clusters skeletons of a monitored person for distinct fall risk discovery and achieved promising results. A more natural setting posed us problems such as ambiguities in class labels and low discrimination power of our original instability features between safe/unsafe skeletons. We validate our three new proposals through evaluation by experiments.

Original languageEnglish
Title of host publicationFoundations of Intelligent Systems - 21st International Symposium, ISMIS 2014, Proceedings
PublisherSpringer Verlag
Pages500-505
Number of pages6
ISBN (Print)9783319083254
DOIs
Publication statusPublished - Jan 1 2014
Event21st International Symposium on Methodologies for Intelligent Systems, ISMIS 2014 - Roskilde, Denmark
Duration: Jun 25 2014Jun 27 2014

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8502 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other21st International Symposium on Methodologies for Intelligent Systems, ISMIS 2014
CountryDenmark
CityRoskilde
Period6/25/146/27/14

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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